Prediktiv analys och kundlojalitet


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Robert Moberg, Prediktiv Analysexpert, IBM Sverige

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Prediktiv analys och kundlojalitet

  1. 1. Prediktiv analys och kundlojalitet Robert MobergPredictive Analytics Solutions Architect
  2. 2. Let me start with a few of qoutes... § ”In the factory we manufacture lipstick, in the store we sell hope” – Charles Revson – 1906 – 1975 – Creater of Revlon § ”People dont want to buy a quarter-inch drill, they want a quarter-inch hole.” – Theodore Levitt – 1925 – 2006 – Harvard Professor § ”We don’t sell an analytics platform – we provide happy, loyal and prospering customers” – Robert Moberg – 1969 – – PASA at IBM
  3. 3. It is not the strongest of the species that survive, nor the most intelligent, but the one most responsive toCharles Darwin change.
  4. 4. A Sample of A Universe of Things That GenerateData Data ?
  5. 5. A Universe of A PredictiveData Model Attributes •Married, 2 kids •Home owner in Liseberg, Älvsjö •Has a house in Gotland •Owns a car •41 years old •Enjoys fine wines and champagne •Plays golf Predicted Attributes •Likes Beastie boys •Likes Gotland •Works long hours •Commutes •Middle Income Predicted Behavior •Dines in descent restaurants •Consumes a lot of electricity •Buys green fees •Family vacations
  6. 6. An Overwhelming Amount of Data to Process High-value, dynamic Social Media - source of competitive differentiation Open-Ended (networks) Surveys Interaction data Attitudinal - E-Mail / chat data transcripts - Opinions - Call center notes - Preferences - Web Click-streams 360 degree - Needs & - In person dialogues Desires Customer View Descriptive data Behavioral - Attributes data - Characteristics - Orders - Self-declared info - Transactions CRM - - Payment Operational Systems (Geo)demographic history Systems s “Traditional - Usage history ”IBM confidential
  7. 7. Evolutionary Solutions for Customer IntimacyDifferentiating Breakaway Foundational Competitive Insight for Decision Makers The Next Best Action
  8. 8. Define the Strategy Run the Business Year Month Week Day Hour No s s s s s w Time to Business ImpactImprove senior management Improve policy makers’ Help individual visibility with decisions with contributors take theKey Performance Predictors Forecasts and Optimization Next Best Action Strategic Tactica Operational l
  9. 9. Predictive Customer AnalyticsPredictive PredictiveOperational Threat and Analytics Risk Analytics
  10. 10. Customer Analytics One to One Research & Purchase Purcha Product Advoc se ate More Produ ct Get Use Customer Prod The Broad Brush Service uct
  11. 11. Operational Analytics Agile Develop ment Procure ment Availab Distributi ility on Long term planning
  12. 12. Risk Analytics Proactive Defin e Allow Monito Preven r t Corrective Detec t
  13. 13. Darwinism according to me: It is not thevData is key strongest of thevUnderstanding data is one thing knowing what to do with itis another species thatvIt’s easier to give people what they want if you know the survive, nor whatthat is most intelligent,vCustomer analytics, a prerequisite to but the one your be relevant to mostcustomers responsive tovCustomer analytics and insights provide decision support Charles Darwin change.vDecisions will be reliable, because they are based on factsnot on speculation Predictive Customer Analytics will make your company responsive to change!!!
  14. 14. TACK